Senior AML Modeling Engineer (Payments & Crypto)
Digital wallet and cryptocurrency exchange platform enabling Filipinos to buy, sell and manage crypto assets with integrated payment services.
About Coins.ph
Coins.ph serves as a regulated crypto platform for over 18 million Filipino users, offering cryptocurrency trading, bill payments, and remittance services. The platform integrates QR payments and mobile load purchases with crypto services, making digital assets accessible to Filipinos.
Skills
About the Role
You will develop and optimize AML risk models combining rule-based engines with machine learning to detect suspicious activity. You will design transaction monitoring strategies covering anomaly detection, transaction structuring, and fund flow analysis. You will analyze on-chain data to track fund movements and identify high-risk address behaviors. You will build user risk scoring systems that integrate KYC, transactional, and blockchain data. You will continuously improve model performance, reduce false positives, and enhance investigation efficiency, ultimately helping to proactively identify high-risk fund flows and complex money laundering activities.
Requirements
- 5+ years of experience in AML / risk modeling (mandatory)
- Proven end-to-end experience in deploying AML models (e.g., transaction monitoring, risk scoring, investigation support)
- Strong proficiency in Python and SQL for data analysis and modeling
- Solid understanding of common AML typologies (e.g., layering, smurfing, cash-out)
- Hands-on experience with machine learning models (e.g., XGBoost, LightGBM)
Responsibilities
- Develop and optimize AML risk models using rule-based engines and machine learning
- Design transaction monitoring strategies including anomaly detection, transaction structuring, and fund flow analysis
- Analyze on-chain data to track fund movements and identify high-risk address behaviors
- Build user risk scoring systems integrating KYC, transactional, and blockchain data
- Continuously improve model performance, reduce false positives, and enhance investigation efficiency
